Topic 20
Topic 20: The Future
Contributors: Nga Pui Leung, JingKai Ong

Topic 1 – Introduction to Social Data Revolution
In this very first class, Andreas presented the idea of social data revolution to the class. We discussed how we can define social data, what values social data adds to our decision-making process, and the central question of individual liberty vs common interests.
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Topic 2 – Data for the People
The class came together for a brainstorming session on how the world would look like in 1, 3, 10, and 30 years from today. Some of the best predictions made by the students include real-time emotional data, the ability to predict symptoms of mental illness through online activities, mass opt out of social media because of data breaches, and mobile integration into the human body.

Topic 3 – 6 Data Rights
The class was introduced to the six data rights proposed by Andreas, and was asked to discuss and rank the six rights in order of their importance. The six data rights are: the right to access data, the right to inspect data companies, the right to amend data, the right to blur data, the right to experiment with data, and the right to port (our data to other companies).
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Topic 4 – Ranking the Data Rights
As an extension to Topic 3, the class was asked to take a step further and rank the six rights in order of their importance. In addition to the 6 rights suggested by Andreas, the class came up with a few other proposed rights such as the right to disconnect data with our identities and private information, the right to sell our own data, and the right to be provided with simple and concise service agreements to avoid confusion and overloading information.

Topic 5 – Sensors and Contexts
The class discussed how reading human minds is made possible by social data and technology. Microexpressions reveal our emotions and thus our thought process, allowing application to read and analyze basic emotions such as amusement, contempt, contentment, embarrassment, excitement, guilt, pride, relief, satisfaction, and shame etc.
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Topic 6 – Data Literacy
Teri Elniski from the Department of Commerce joined the class for a discussion on data literacy. The students had an in-class activity that involves developing and presenting ideas on the best usages of the Census data. The class agreed that data literacy is becoming increasingly important, and that core data skills should be included in formal education.

Topic 7 – Social Data for Social Science
Dr. Qing Wu from Google introduced to the class some useful tools developed by Google that can help us better understand data. Some existing tools include Google Trends, Google Correlate, Google Consumer Surveys, and Google Analytics Solutions.
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Topic 8 – Predicting the Present
Dr. Qing Wu demonstrated to the class how one could use aggregated data about the past to contextualize and “predict the present”. However, some drawbacks were also discussed, such as the limitations of using data as correlation does not equal causation, and the fact that many of the analysis conducted were made possible only if one has access to the internal API of companies.

Topic 9 – People for the Data
Dr. Qing Wu had a panel discussion with Andreas in this class, talking about the sexiest job of the 21st century – data scientist. The class benefited a lot from excellent insights on what makes a good data scientist and how we could utilize private data sources for the public good (thereby having people for the data ensuring data for the people).

Topic 10 – Asking Good Questions
Ming Yeow Ng, the cofounder of Minute, delivered a presentation entitled: “The Human Experience: Why questions lie at the heart of social data”. In this session, Ming Yeow talked about questions frame, questions bond, questions spawn, and questions lead. One of the important takeaways from his presentation is that good questions can stimulate ideas and deepen intimacy.

Topic 11 – Learning Equations
During this topic, we discussed our views on the flawed education system of assessing students’ understanding of the material through tests scores and evaluating teachers’ teaching based on students’ perception of the teachers. Andreas’ SDR class differs from other classes in the metrics and methods he uses to engage his students, optimize learning, receive (weekly) feedback for improvement, and maintain the quality of speakers.
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Topic 12 – Yelp
Yelp’s representatives shared with us how Yelp uses and experiments with data to strengthen the trust of its users and its company’s credibility by confirming business locations and ensuring the quality and trustability of reviews and photos, enhance user experience by improving the search function, matching users with businesses, quarantining spammers, and using A/B testing to increase ad promotion to gain most of its revenue.
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Topic 13 – Cam4
Cam4 is a pioneer porn site in that it allows the user to personalize the type of content, community, acts, and location of porn (s)he is interested in instead of recommending the most popular porn stars and brings the users closer to the real actors by offering an option to connect and build relationships unlike traditional porn sites where users are limited to just viewing porn. Cam4’s data collection on its performers and users are revealing interesting trends and insights on human psychology and social interactions that haven’t been openly available/known before.

Topic 14 – Cam4 Reflection
We discussed the morals and ethics behind Cam4’s services after reflecting on the data rights -- transparency and agency -- we learned in the previous classes. Unlike the previous presentations that we’ve seen where companies seem to be exploiting user data for profit, Cam4 is building a community and giving unemployed, financially struggling people the opportunity to improve their conditions by selling their bodies, a topic that has been debated for a long time whether it is ethical.

Topic 15 – Surveillance
Protection of privacy has alway been kept in place by the balance between 3 forces -- lack of resources, law, and public pressure, but the balance has been upset because of the rise in innovation within the IT sector. The American Civil Liberties Union (ACLU)’s goal is to fight against the government and corporate actions that violate privacy and inform unknowing customers of legal loopholes that exploit their privacy.
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Topic 16Stealth
We participated in experiments where one group had to perform illicit activities and avoid surveillance given a scenario, i.e. sneaking a USB containing confidential information to Edward Snowden and laundering money, and another group had to devise a plan to crackdown on these stealthy acts. These simulations walked us through the difficulties of hiding our digital traces, identity, etc. in a data and digital age.
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Topic 17Blockchain
Blockchain’s objective is to act as a public ledger of all transactions to create a system of checks and balances so that all participating parties regulate each other and no single party dominates. Blockchain has inspired many other companies because of its novelty in openness to anyone that stores a set of verified transactions and its database that need to be updated by proof-of-work or some other method of distributed consensus.

Topic 18Transparency
Glassdoor levels the playing field for individuals vs. companies by employing a “give to get” model for users to increase transparency and sharing of information about companies, employers, salaries, holidays, work environment, treatment of workers, interviews, etc. anonymously. This puts pressure on the corporations to change their work conditions, hiring and training processes, etc. and stigmatize those that appear to practice gender wage inequality based on Glassdoor’s algorithms.
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Topic 19Retail
Dynamic Action provides a platform that combines enterprise applications and cloud retail systems by utilizing big data technologies to determine how to take and use merchandising data, customer data, web analytics, exposure, and inventory data to help retailers run their businesses better. Macy’s is another corporation that has been using consumer data and behavior to better user experience and generate revenue by decreasing rates of customer returns and helping customers find the best match.
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